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Russian mathematician finds new approach to 190-year-old 'eternal' math problem
A Russian mathematician has developed a new method for analyzing a class of equations that underpin models in physics and ...
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
From computers to smartphones, from smart appliances to the internet itself, the technology we use every day only exists ...
ABSTRACT: The diversity of snail intermediate hosts of schistosomes and infection rates are influenced by environmental determinants. Knowledge of these local environmental determinants is an ...
Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...
Original Paper from Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation (NeurIPS 2023). This version uses outdated gym / numpy / mujoco versions therefore I updated and ...
Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values ...
ABSTRACT: Continuous groundwater quality monitoring poses significant challenges affecting the environment and public health. Groundwater in Abidjan, specifically from the Continental Terminal (CT), ...
Multi-layer perceptrons (MLPs), or fully-connected feedforward neural networks, are fundamental in deep learning, serving as default models for approximating nonlinear functions. Despite their ...
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